Assessment of snow model uncertainty in relation to the effect of a 1 °C warming using the snow modelling framework openAMUNDSEN

Abstract. Novel climate model data at the kilometer-scale, innovative downscaling techniques, sophisticated snow modelling frameworks, and increasing computational capacities are among the elements currently paving the way for a new phase in high resolution and physically based climate impact studies on snow hydrology in complex mountain terrain. While the assessment of climate model uncertainty is well established, the uncertainty arising from snow model selection typically receives far less attention. To investigate the uncertainty induced by the selection of the snow model configuration, we simulate the seasonal snow cover in the complex mountain area of the Berchtesgaden National Park mountains (Germany) under historical conditions (October 2013–September 2023) and for a 10 year period characterized by a 1 °C warming, using a large number of openAMUNDSEN snow model configurations (n=108) with degree-day as well as physically based snowmelt methods and varying land cover maps and spatial resolutions. The analysis of the resulting snow cover durations and snow disappearance days indicates that differences due to the choice of snowmelt method, land cover map and spatial resolution can be comparable in magnitude to the effect of a 1 °C warming, with uncertainties particularly pronounced in the forested areas and in the high elevations of the study area. Our results support the identification of critical snow model settings that need careful consideration, especially when employing energy balance instead of degree-day snow models to investigate climate change impacts on snow hydrology in complex mountain terrain.